Final answer:
Memory optimized instances are ideal for applications requiring high memory bandwidth, such as high-performance relational and NoSQL databases, distributed cache stores, in-memory databases, real-time big data processing, HPC, and EDA.
Step-by-step explanation:
The memory optimized instances are designed to cater to workloads that require high memory bandwidth and low-latency access to in-memory data. These instances are well-suited for a range of applications, including high-performance databases like MySQL and NoSQL options such as MongoDB and Cassandra. They are also ideal for distributed web scale cache stores like Memcached and Redis, that handle in-memory caching of key-value data.
Furthermore, they are effective for in-memory databases which use optimized data storage formats, and can aid significantly in analytics for business intelligence purposes such as those used by SAP HANA. For real-time processing of big unstructured data, often seen in financial services, or when using Hadoop/Spark clusters, these instances provide the necessary computing power. They are equally suitable for high-performance computing (HPC) tasks, as well as Electronic Design Automation (EDA) applications that demand fast processing capabilities.